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Internship in AI & Machine Learning
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- New graduates
- For current students
Enrolled in a Bachelor’s or Master’s program in computer science, mathematics, physics, AI, or related fields
What you’ll work on
Full postingPrepare samples and acquire data in the laboratory
Curate, structure, and version datasets for reproducible experiments
Build data preprocessing pipelines for AI and machine learning workflows
Generate and evaluate simulation-based or synthetic data
Automate embedded-device tests and optimize accuracy and speed
From the employer’s posting
Be involved in sample preparation and data acquisition in the laboratory for full data ownership
Curate, structure, and version datasets for reproducible experiments
Build data preprocessing pipelines for AI and machine learning workflows
Generate and evaluate simulation-based or synthetic data
Automate embedded-device tests and optimize accuracy and speed
Education & alternatives
Your Profile - Enrolled in a Bachelor’s or Master’s program in computer science, mathematics, physics, AI, or related fields - Strong programming skills in Python and PyTorch
Posting record
Report an errorActively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 27, 20268 days ago
- Recorded sightings
- 13
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Zeissgroup is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- PyTorch
Where the posting names them
- Enrolled in a Bachelor’s or Master’s program in computer science, mathematics, physics, AI, or related fields - Strong programming skills in Python and PyTorch - Solid understanding of software development principles
Your next step
Complete your application on zeissgroup.wd3.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Motivation of the Work
Turning today’s research into tomorrow’s applications, together. At ZEISS, we focus on user-centric innovation to transform ideas into cutting-edge solutions. The ZEISS Innovation Hub @ KIT brings together students, researchers, and industry professionals to advance AI, computer vision, and machine learning in application-oriented projects.
Your Role
We are looking for highly motivated students to develop AI-based solutions for real-world vision tasks, including agricultural solutions, from data collection, simulation-based data generation, and model development to deployment on target devices. This internship provides hands-on experience across the full ML pipeline, including vision foundation models, data preprocessing and curation, quantization-aware training, edge-device deployment, and performance evaluation.
- Develop an efficient and reproducible workflow for application-oriented machine learning solutions.
- Be involved in sample preparation and data acquisition in the laboratory for full data ownership
- Implement quantitative metrics to assess and optimize data preprocessing quality and guide relabeling efforts
- Curate, structure, and version datasets for reproducible experiments
- Build data preprocessing pipelines for AI and machine learning workflows
- Generate and evaluate simulation-based or synthetic data
- Run hyperparameter and model studies in a traceable environment.
- Automate embedded-device tests and optimize accuracy and speed.
We Offer
- A dynamic and interdisciplinary environment
- Hands-on experience with real-world image, sensor, and simulation-based data, foundation models, model quantization, and edge deployment
- Learn how to set up a full machine learning pipeline
- Close mentorship from experts in deep learning
- An agile work environment
- Enrolled in a Bachelor’s or Master’s program in computer science, mathematics, physics, AI, or related fields
- Strong programming skills in Python and PyTorch
- Solid understanding of software development principles
- Fundamental knowledge of data preprocessing steps for computer vision and vision foundation models
- Familiarity with AI/ML concepts (e.g., supervised learning, deep learning architectures) is a plus
- Experience with edge-device deployment and model quantization is a plus
- Creative, pragmatic, and self-motivated with strong analytical skills
- Capable of working independently as well as in a team-oriented environment
- Excellent communication skills in English or German
- Passion for innovation, enthusiasm for new technologies, and motivation to contribute to interdisciplinary projects
Sounds exciting? Then become part of #teamZEISS and help us shape the future! Please provide your complete application documents (CV, transcript of records, etc.).
Your ZEISS Recruiting Team:
Selina SafradinSource details
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- Pay
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- Location & working pattern
Karlsruhe
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